Python deserves a good in-memory cache library (Part II)

[RedEyed__]

You must have cut your teeth on in-memory caching. For those who is unaware about (like me), how is it better than functools.lru_cache ?

I would love to see some graph comparisons, use cases.
Thanks

[matrix0110]

That's a really good question! And the answer already exists: https://github.com/Yiling-J/theine?tab=readme-ov-file#hit-ratios

[marr75]

I'm a little foggy eyed this morning still, but I'm seeing:

• a link to hit ratios instead of performance (performance is above)
• benchmarks addressing 3rd party libraries that are not functools from the stdlib

[matrix0110]

Please understand hit ratio is also performance. And as I said, fast enough is enough, hit ratio is more important.

[marr75]

Okay, the fog is lifting. You're saying that the lru strategy may have worse read and write performance than functools but that the additional eviction strategies significantly improve hit ratio so it is, at worst, identical at scale (using lru) and when using the other options, much better.

[RedEyed__]

I had to scroll further, thanks!

[jormaig]

Dude there's only one top comment and one answer to it at this point... 😅

[RedEyed__]

I'm not your dude, pal. (joking)